{"title":"Improved genetic algorithm for economic load dispatch with valve-point loadings","authors":"S. Ling, H.K. Lam, F. Leung, Y.S. Lee","doi":"10.1109/IECON.2003.1280021","DOIUrl":null,"url":null,"abstract":"Economic load dispatch is one of the optimization problems in power systems. This paper presents an improved genetic algorithm for economic load dispatch with valve-point loadings. New crossover and mutation operations are introduced. The solutions of the economic load dispatch with valve-point loadings under three cases are solved by the improved genetic algorithm. Test results are given and compared with those from different published genetic algorithms. It is shown that the proposed improved genetic algorithm performs better than the published genetic algorithms.","PeriodicalId":403239,"journal":{"name":"IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.2003.1280021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
Economic load dispatch is one of the optimization problems in power systems. This paper presents an improved genetic algorithm for economic load dispatch with valve-point loadings. New crossover and mutation operations are introduced. The solutions of the economic load dispatch with valve-point loadings under three cases are solved by the improved genetic algorithm. Test results are given and compared with those from different published genetic algorithms. It is shown that the proposed improved genetic algorithm performs better than the published genetic algorithms.